def verb_proc(self, id, point, sep):
self.v_predicates = []
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
lex_score = verb['lex']
srl_score = verb['srl']
combo_score = verb['combo']
(vt, vh) = verb['tokens']
#TODO VN isec, expand VO
vt_tool = VerbTools(vt)
i = '%s%s%s' % (self.clean_str(vt), sep, self.clean_str(vh))
vh_tool = VerbTools(vh)
vt_classes = vt_tool.vn_classes()
vh_classes = vh_tool.vn_classes()
vt_classes.extend(vh_classes)
set_classes = set(vt_classes)
vt_vh_rel = vt_tool.verb_relations(vh)
verb_sim = VerbMetrics(text_v=vt, hypo_v=vh)
vn = verb_sim.vn_isec()
d = verb_sim.direct()
vo = verb_sim.vo()
#token_verb = 'TokenVerb(%s, "%s%s%s")'%(i, self.clean_str(vt), sep, self.clean_str(vh))
sim_vn = '>sim_vn\n"%s" %s' % (i, vn)
sim_vo = '>sim_vo\n"%s" %s' % (i, vo)
sim_d = '>sim_d\n"%s" %s' % (i, d)
str_classes = sep.join(set_classes)
bow_vn = '>bow_vn\n"%s" "%s"' % (i,
self.clean_str(str_classes))
if srl_score > lex_score:
st = 1
else:
st = 0
strong_context = '>strong_con\n"%s" %s' % (i, st)
verb_id = '>verb\n"%s" %s' % (i, id)
#if str_classes != "":
self.v_predicates.append(bow_vn)
self.v_predicates.append(strong_context)
self.v_predicates.append(sim_vn)
self.v_predicates.append(sim_vo)
self.v_predicates.append(sim_d)
#self.v_predicates.append(token_verb)
self.v_predicates.append(verb_id)
return self.v_predicates
def verb_proc(self, id, point, sep):
self.v_predicates = []
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
lex_score = verb['lex']
srl_score = verb['srl']
combo_score = verb['combo']
(vt, vh) = verb['tokens']
#TODO VN isec, expand VO
vt_tool = VerbTools(vt)
i = '%s%s%s'%(self.clean_str(vt), sep, self.clean_str(vh))
vh_tool = VerbTools(vh)
vt_classes = vt_tool.vn_classes()
vh_classes = vh_tool.vn_classes()
vt_classes.extend(vh_classes)
set_classes = set(vt_classes)
vt_vh_rel = vt_tool.verb_relations(vh)
verb_sim = VerbMetrics(text_v=vt, hypo_v=vh)
vn = verb_sim.vn_isec()
d = verb_sim.direct()
vo = verb_sim.vo()
#token_verb = 'TokenVerb(%s, "%s%s%s")'%(i, self.clean_str(vt), sep, self.clean_str(vh))
sim_vn = '>sim_vn\n"%s" %s'%(i, vn)
sim_vo = '>sim_vo\n"%s" %s'%(i, vo)
sim_d = '>sim_d\n"%s" %s'%(i, d)
str_classes = sep.join(set_classes)
bow_vn = '>bow_vn\n"%s" "%s"'%(i, self.clean_str(str_classes))
if srl_score > lex_score:
st = 1
else:
st = 0
strong_context = '>strong_con\n"%s" %s'%(i, st)
verb_id = '>verb\n"%s" %s'%(i, id)
#if str_classes != "":
self.v_predicates.append(bow_vn)
self.v_predicates.append(strong_context)
self.v_predicates.append(sim_vn)
self.v_predicates.append(sim_vo)
self.v_predicates.append(sim_d)
#self.v_predicates.append(token_verb)
self.v_predicates.append(verb_id)
return self.v_predicates
def verb_proc(self, id, point, sep):
self.v_predicates = []
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
lex_score = verb['lex']
srl_score = verb['srl']
combo_score = verb['combo']
(vt, vh) = verb['tokens']
vt_tool = VerbTools(vt)
i = '%s.%s'%(id, i)
vh_tool = VerbTools(vh)
vt_classes = vt_tool.vn_classes()
vh_classes = vh_tool.vn_classes()
vt_classes.extend(vh_classes)
set_classes = set(vt_classes)
vt_vh_rel = vt_tool.verb_relations(vh)
verb_sim = VerbMetrics(text_v=vt, hypo_v=vh)
vn = verb_sim.vn_isec()
d = verb_sim.direct()
vo = verb_sim.vo()
token_verb = 'TokenVerb(%s, %s, "%s%s%s")'%(i, id, self.clean_str(vt), sep, self.clean_str(vh))
sim_vn = 'SimVN(%s, %s, %s)'%(i, id, vn)
sim_vo = 'SimVO(%s, %s, %s)'%(i, id, vo)
sim_d = 'SimD(%s, %s, %s)'%(i, id, d)
str_classes = sep.join(set_classes)
bow_vn = 'BowVN(%s, %s, "%s")'%(i, id, self.clean_str(str_classes))
if srl_score > lex_score:
st = 1
else:
st = 0
strong_context = 'StrongCon(%s, %s, %s)'%(i, id, st)
self.v_predicates.append(bow_vn)
self.v_predicates.append(strong_context)
self.v_predicates.append(sim_vn)
self.v_predicates.append(sim_vo)
self.v_predicates.append(sim_d)
self.v_predicates.append(token_verb)
return self.v_predicates
class Edistance:
def __init__(self,
frames_text={},
tokens_text=[],
chunks_text=[],
frames_hypo={},
tokens_hypo=[],
chunks_hypo=[],
e_type='simple',
verbose=1,
entailment=-1):
self.e_type = e_type
self.srl_t = SRLTools()
self.srl_h = SRLTools()
self.verb_net = VerbMetrics()
self.arg_sim = SetMetrics()
self.lin = Lin()
self.wn = WNTools()
self.frames_hypo = frames_text
self.frames_text = frames_hypo
self.tokens_hypo = tokens_hypo
self.tokens_text = tokens_text
self.chunks_hypo = chunks_hypo
self.chunks_text = chunks_text
self.args_text = {}
self.args_hypo = {}
self.verbs_text = []
self.verbs_hypo = []
self.edit_score = 0
self.verb_score = 0
self.chunk_score = 0
self.oper_type = {'del': 0, 'in': 0, 'sub': 0}
self.verbose = verbose
self.entailment = entailment
return
def get_edistance_micai(self,
frames_text={},
tokens_text=[],
chunks_text=[],
frames_hypo={},
tokens_hypo=[],
chunks_hypo=[],
entailment=-1):
if frames_text:
self.frames_text = frames_text
if frames_hypo:
self.frames_hypo = frames_hypo
if tokens_text:
self.tokens_text = tokens_text
if tokens_hypo:
self.tokens_hypo = tokens_hypo
if chunks_text:
self.chunks_text = chunks_text
if chunks_hypo:
self.chunks_hypo = chunks_hypo
if entailment:
self.entailment = entailment
self.srl_t.set_frames(self.frames_text)
self.srl_h.set_frames(self.frames_hypo)
self.srl_t.set_tokens(self.tokens_text)
self.srl_h.set_tokens(self.tokens_hypo)
self.args_text = self.srl_t.get_words_frame()
self.args_hypo = self.srl_h.get_words_frame()
sum_verb = 0
num_verbs_h = len(self.args_text.keys())
self.__p_stderr(
'###V(%s)###\nT:%s\nH:%s\n' %
(self.entailment, ' '.join(tokens_text), ' '.join(tokens_hypo)))
self.edit_score = 0
for verb_t, args_t in self.args_text.items():
for verb_h, args_h in self.args_hypo.items():
sim_verbs = self.__simVerbs(verb_t, verb_h)
if sim_verbs == 1:
#sim verbs
self.__p_stderr('\tverbs(%s, %s)\n' % (verb_t, verb_h))
if self.e_type == 'simple':
self.edit_score += self.__simpleARG(args_t, args_h)
self.edit_score = float(self.edit_score) / num_verbs_h
self.__p_stderr('\ted_score(%s)\n' % (self.edit_score))
if self.edit_score == 0.0:
self.edit_score = self.__back_off_order(self.chunks_text,
self.chunks_hypo)
#if edit_score == 0 go for chunk backoff
return self.edit_score
def __simpleARG(self, args_t=[], args_h=[]):
score = 1.0
oper_sum = 0
tags_t = self.__extract_tags(args_t)
tags_h = self.__extract_tags(args_h)
self.oper_type = {'del': 0, 'in': 0, 'sub': 0}
#look for sub
for tag_t, tokens_t in tags_t.items():
for tag_h, tokens_h in tags_h.items():
if tag_t == tag_h: # same tag
if ' '.join(tokens_t) != ' '.join(tokens_h):
self.oper_type['sub'] += 1 #subtitution
self.__p_stderr('\t\toper(sub): [%s] %s -> %s\n' %
(tag_t, tokens_t, tokens_h))
oper_sum += 1
#look for insertion
for tag_t, tokens_t in tags_t.items():
if not tag_t in tags_h: # insertion
self.oper_type['in'] += 1
self.__p_stderr('\t\toper(in): [%s] %s\n' %
(tag_t, tags_t[tag_t]))
oper_sum += 1
#look for deletion
for tag_h, tokens_h in tags_h.items():
if not tag_h in tags_t: # deletion
self.oper_type['del'] += 1
self.__p_stderr('\t\toper(del): [%s] %s\n' %
(tag_h, tags_h[tag_h]))
oper_sum += 1
self.__p_stderr('num oper: %s\n' % self.oper_type)
self.__p_stderr('sum oper: %s\n' % oper_sum)
if oper_sum == 0:
return 0
else:
score = score / float(oper_sum)
self.__p_stderr('simp_score: %s\n' % score)
return score
def __extract_tags(self, args):
tags = {}
for tag, tokens in args:
tags[tag] = tokens
return tags
def __simVerbs(self, verb_t='', verb_h=''):
if verb_t == verb_h:
return 1
self.verb_net.set_text_verb(verb_t)
self.verb_net.set_hypo_verb(verb_h)
isec = self.verb_net.vn_isec()
if isec == 0:
vo = self.verb_net.vo()
return vo
else:
return isec
def __back_off_order(self, chunks_t=[], chunks_h=[]):
score = 0
sum_ch = 0
self.__p_stderr('chunk back-off\n')
chunks_t = chunks_t.pos()
chunks_h = chunks_h.pos()
for i, chunk_h in enumerate(chunks_h):
try:
(node_t, tag_t) = chunks_t[i]
(node_h, tag_h) = chunk_h
if tag_t == tag_h:
(word_t, pos_t) = node_t
(word_h, pos_h) = node_h
if word_t == word_h:
sum_ch += 1.0
self.__p_stderr('\t[%s]: %s\n' % (tag_t, word_t))
else:
sum_ch += 0.5
self.__p_stderr('\t[%s|%s]: %s %s \n' %
(tag_t, sum_ch, word_t, word_h))
except:
sum_ch += 0.0
score = float(sum_ch) / len(chunks_h)
return score
def __p_stderr(self, text=''):
if self.verbose == 1:
sys.stderr.write(text)
return
class TineVN:
def __init__(self, frames_text = {}, tokens_text = [], frames_hypo = {}, tokens_hypo = [], sim_type = 'Lin', verbose = 1):
self.srl_t = SRLTools()
self.srl_h = SRLTools()
self.verb_net = VerbMetrics()
self.arg_sim = SetMetrics()
self.lin = Lin()
self.wn = WNTools()
self.frames_hypo = frames_text
self.frames_text = frames_hypo
self.tokens_hypo = tokens_hypo
self.tokens_text = tokens_text
self.args_text = {}
self.args_hypo = {}
self.verbs_text = []
self.verbs_hypo = []
self.tine_score = 0
self.verb_score = 0
self.arg_score = 0
self.sim_type = sim_type
self.verbose = verbose
#self.pos_text = pos_text
#self.pos_hypo = pos_hypo
return
def get_tine_score(self, frames_text = {}, tokens_text = [], frames_hypo = {}, tokens_hypo = []):
if frames_text:
self.frames_text = frames_text
if frames_hypo:
self.frames_hypo = frames_hypo
if tokens_text:
self.tokens_text = tokens_text
if tokens_hypo:
self.tokens_hypo = tokens_hypo
self.srl_t.set_frames(self.frames_text)
self.srl_h.set_frames(self.frames_hypo)
self.srl_t.set_tokens(self.tokens_text)
self.srl_h.set_tokens(self.tokens_hypo)
self.args_text = self.srl_t.get_words_frame()
self.args_hypo = self.srl_h.get_words_frame()
sum_verb = 0
num_verbs_h = len(self.args_text.keys())
self.__p_stderr('TINE VerbNet\n')
self.__p_stderr('T: %s \n H: %s\n'%(self.args_text, self.args_hypo))
self.__p_stderr('T: %s \n H: %s\n'%(self.args_text.keys(), self.args_hypo.keys()))
for verb_t, args_t in self.args_text.items():
for verb_h, args_h in self.args_hypo.items():
sim_verbs = self.__simVerbs(verb_t, verb_h)
if sim_verbs == 1:
self.__p_stderr('verbs(%s, %s)\n'%(verb_t, verb_h))
args_score = self.__simArgs(args_t, args_h)
sum_verb += args_score
self.tine_score = float(sum_verb) / num_verbs_h
self.__p_stderr('score:%s\n'%(self.tine_score))
return self.tine_score
def __simVerbs(self, verb_t = '', verb_h = ''):
if verb_t == verb_h:
return 1
self.verb_net.set_text_verb(verb_t)
self.verb_net.set_hypo_verb(verb_h)
isec = self.verb_net.vn_isec()
if isec == 0:
vo = self.verb_net.vo()
return vo
else:
return isec
return isec
def __simArgs(self, args_t = [], args_h = []):
sum_args = 0
num_args_h = len(args_h)
for tag_t, tokens_t in args_t:
for tag_h, tokens_h in args_h:
if tag_t == tag_h:
expand_t = []
expand_h = []
if self.sim_type == 'Lin':
expand_t = self.lin.expand_bow(tokens_t)
expand_h = self.lin.expand_bow(tokens_h)
elif self.sim_type == 'WN':
expand_t = self.wn.expand_bow_tree(tokens_t)
expand_h = self.wn.expand_bow_tree(tokens_h)
self.arg_sim.set_text(expand_t)
self.arg_sim.set_hypo(expand_h)
self.arg_score = self.arg_sim.cosine()
self.__p_stderr('\t[%s|%s] %s %s\n'%(tag_t, self.arg_score, expand_t, expand_h))
sum_args += self.arg_score
if num_args_h == 0:
return 0
else:
self.verb_score = float(sum_args) / num_args_h
return self.verb_score
def __p_stderr(self, text = ''):
if self.verbose == 1:
sys.stderr.write(text)
return
def get_verb_score(self):
return self.verb_score
def get_arg_score(self):
return self.arg_score